Wind Turbines: Innovative Concepts

Transcription

1 Downloaded from orbit.dtu.dk on: Jan 21, 2019 Wind Turbines: Innovative Concepts Henriksen, Lars Christian Publication date: 2013 Link back to DTU Orbit Citation (APA): Henriksen, L. C. (Author). (2013). Wind Turbines: Innovative Concepts. Sound/Visual production (digital) General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

2 Wind Turbines: Innovative Concepts Lars Christian Henriksen, DTU Wind Energy Wind Energy Theme Day for Industry: Control hi [13] The Nordic Expo, Herning, September 4 th 2013

3 Outline Model-based control Basics: State estimation, LQ/MPC control Control Design Model Example: Dynamic Inflow Trailing edge flaps The concept Combining trailing edge flaps and IPC LiDAR enhanced control Load alleviation Power optimization Passive vs. active control Bend-twist couplings Floating wind turbines Using an Extended Kalman Filter for state estimation 2 DTU Wind Energy, Technical University of Denmark

4 Model-based Control 3

5 Model-based Control Control Methods applied on Wind Turbines Classic Control Methods PI Control Interconnected PI Controllers and Bandpass Filters... Modern Control Methods Linear Quadratic Control (LQ) Linear Parameter Varying Control (LPV) Robust Control (H 2,H ) Model Predictive Control (MPC) Misc. Nonlinear Control Methods... Individual Pitch Coleman/Multi-blade Coordinate Transformation Decoupling of control loops... Trailing edge flaps Decoupling of control loops... LiDAR Feed forward of measure wind... DTU Wind Energy, Technical University of Denmark

6 Model-based Control Control Theory in Time Discrete Form State space model x(t k+1 ) = f(x(t k ),u(t k )) + w(t k ) y(t k ) = g(x(t k ),u(t k )) + v(t k ) State estimator x(t k t k ) = x(t k t k-1 ) + L [y(t k ) - g(x(t k t k-1 ),u(t k ))] x(t k+1 t k ) = f(x(t k t k ),u(t k )) State space controller u(t k ) = K x(t k t k ) or u(t k ) = K x(t k t k-1 ) or u(t k ) = k(x(t k t k-1 )) or... x State Estimator ( KF or...) State space Controller (MPC or...) y and u u Plant (Wind Turbine) Disturbances: w and v (Turbulent Wind, Wave forces,...) DTU Wind Energy, Technical University of Denmark

7 Model-based Control Control Design Model The control design model is a set of linear/nonlinear ordinary differential equations (in state space form), which are adequately describing the system to be controlled. Adequately means including phenomena of interest (tower DOFs, blade DOFs etc.) in a frequency range of interest. The control design model can be obtained from first-principles modeling, system identification (black box), a combination of the two (gray box). A first-principles model of a wind turbine can be obtained from aeroelastic software codes such as Bladed, FAST, HAWCStab2 etc. 6 DTU Wind Energy, Technical University of Denmark

8 Model-based Control Control Design Model Bode plots From collective blade pitch to generator speed 8 m/s 16 m/s 7 DTU Wind Energy, Technical University of Denmark

9 Model-based Control Dynamic Inflow 8 DTU Wind Energy, Technical University of Denmark

10 Trailing Edge Flaps 9

11 Trailing Edge Flaps The CRTEF Development Comsol 2D analyses 10 DTU Wind Energy, Technical University of Denmark

12 Trailing Edge Flaps Wind tunnel experiment Dec two different inflow sensors 11 DTU Wind Energy, Technical University of Denmark

13 C L [-] [deg] Trailing Edge Flaps Comparison of measurements and model =8deg Flap SG [deg] time [s] 12 DTU Wind Energy, Technical University of Denmark

14 Trailing Edge Flaps Test rig Pressure measurements Test rig based on a 100 kw turbine. Rotation of a 10m long tube with an airfoil section of about 2x1m Pitch actuator 13 DTU Wind Energy, Technical University of Denmark

15 Trailing Edge Flaps Simulation Test Case Reference NREL 5 MW turbine Adaptive Trailing Edge Flaps All flaps on one blade moved as one Sensors: Shaft sp., Blade root b.mom, Tower top acc. Simulations with HAWC2 Multibody dynamics, includes torsion Unsteady BEM aerodynamics IEC conditions: class A. Iref:0.16 (wsp: 18 m/s) Focus on blade load alleviation 14 DTU Wind Energy, Technical University of Denmark

16 Trailing Edge Flaps Combined IPC and Trailing Edge Flap Control 15 PI 0.3 DTU Wind Energy, Technical University of Denmark Combined Pitch and ATEFs control

17 LiDAR Enhanced Control 16

18 LiDAR Enhanced Control Types and objectives Load alleviation Collective pitch control (CPC) Individual pitch control (IPC) Power optimization Tracking optimal operation point Reducing yaw misalignment Nacelle mounted (mounted on top of nacelle) Spinner/hub mounted Blade mounted (instead of pitottubes) 17 DTU Wind Energy, Technical University of Denmark

19 LiDAR Enhanced Control Uncertainties and Limitations LiDAR uncertainties Validity of Taylors hypothesis of frozen turbulence Volume average of wind speed measurements Projection error Measurement availability and system reliability 18 DTU Wind Energy, Technical University of Denmark

20 LiDAR Enhanced Control Collective Pitch Control D. Schlipf et al., Experimental results shows that fatique loads of CART2 turbine can lowered by introducing LiDAR based feed-forward collective pitch control E. Bossanyi et al., DTU Wind Energy, Technical University of Denmark

21 LiDAR Enhanced Control Individual Pitch Control K. A. Kragh et al., 2013 LiDAR based feed-forward IPC is mainly beneficial in situations with rapid, smal scale variations (e.g. changing wind shear). Very sensitive to uncertainties relating to the inflow estimation 20 DTU Wind Energy, Technical University of Denmark

22 Passive vs. Active Control 21

23 Passive vs. Active Control Overview Passive control methods Swept blades Bend-twist couplings Active control methods Individual pitch control Trailing edge flap control 22 DTU Wind Energy, Technical University of Denmark

24 Passive vs. Active Control Issues Many aero-elastic tools needs further development to handle complex beam models. Can the blades be fabricated such that they behave as predicted by the aero-elastic tools. Further development of control methods is needed. Developed control methods should be adopted by industry. 23 DTU Wind Energy, Technical University of Denmark

25 Floating Wind Turbines 24

26 Floating Wind Turbines The Hywind Concept 25 DTU Wind Energy, Technical University of Denmark

27 Floating Wind Turbines Simulations of the Hywind Concept (I) Wind turbine states 1 or 2 tower fore-aft DOF 1 or 2 tower side-side DOF 2 blade edge-wise DOF pr. blade 2 blade flap-wise DOF pr. Blade 1 induced wind speed state pr. blade Disturbance states 1 wind speed (2 nd order) pr. blade 1 fore-aft hydrodynamic force (2 nd order) 1 side-side hydrodynamic force (2 nd order) Sensors used by the EKF Pitch angles of each blade Electro magnetic generator torque Generator power Generator speed Rotor speed Tower top fore-aft acceleration Tower top side-side acceleration Flap-wise blade root bending moment at each blade Edge-wise blade root bending moment at each blade 26 DTU Wind Energy, Technical University of Denmark

28 Floating Wind Turbines Simulations of the Hywind Concept (II) 27 DTU Wind Energy, Technical University of Denmark

29 Floating Wind Turbines Simulations of the Hywind Concept (III) 28 DTU Wind Energy, Technical University of Denmark

30 Floating Wind Turbines The WindFloat Concept 29 DTU Wind Energy, Technical University of Denmark

31 Industrial/academic Cooperation 30

32 Industrial/academic Cooperation Foundations for offshore wind turbines (incl. floating concepts) Trailing edge flaps LiDARs Pitch gears Drive train gears Aerodynamic blade design Structural blade design Materials research both composites and alloys/metals Wind Recourse Assessments Measurement campaigns for wind turbines High altitude wind energy converters (Kites and lighter than air devices) 31 DTU Wind Energy, Technical University of Denmark

33 Conclusions Good mathematical models of systems and components are required both for control design purposes but also for evaluation of performance/behavior. Many innovative concepts have been and will be tested and developed, some will mature for commercial success and some will be forgotten, only to be presented as innovations a decade later. Cost-of-energy (COE) is ultimately the main driver determining whether or not an innovation will reach a commercial state. Academic cooperation is good way to test some of the innovative ideas before spending to much time and money on the idea. 32 DTU Wind Energy, Technical University of Denmark

34 Thank you for your attention! 33